docstr: Instance-level negative likelihood ratios. 
docstr_tok: ["Instance-level","negative","likelihood","ratios","."]
code: def instance_score(
      self, X: np.ndarray, batch_size: int = int(1e10)
  ) -> np.ndarray:
      """Instance-level negative likelihood ratios."""
      return -self.llr(X, False, batch_size=batch_size)
  
imports: from functools import partial
  import logging
  import numpy
  import tensorflow
  from tensorflow.keras.layers import Input
  from tensorflow.keras.models import Model
  from tensorflow_probability.python.distributions.distribution import Distribution
  from typing import Callable, Dict, Tuple, Union
  from alibi_detect.models.tensorflow.pixelcnn import PixelCNN
  from alibi_detect.models.tensorflow.trainer import trainer
  from alibi_detect.base import BaseDetector, FitMixin, ThresholdMixin, outlier_prediction_dict
  from alibi_detect.utils.tensorflow.prediction import predict_batch
  from alibi_detect.utils.tensorflow.perturbation import mutate_categorical
  from alibi_detect.utils._types import OptimizerTF
label_desc: Use image node_id 8 for calling the LLR obj's underlying member method code with example usage: obj.instance_score(X, batch_size) and returns: unknown